556 Reading
arbitrary features of experience rather than being things
like words or letters (Harm & Seidenberg, 1999; Plaut,
McClelland, Seidenberg, & Patterson, 1996; Seidenberg &
McClelland, 1989). For this process to work rapidly enough
for one to recognize a word in a fraction of a second, these
models all assume that this contact between the current stim-
ulus and memory must be in parallelacross all these features.
For this reason, these models are often termed parallel
distributed processing (PDP) models. Resonance models
(Stone & Van Orden, 1994; Van Orden & Goldinger, 1994)
are a similar class of models that posit a somewhat different
type of internal memory structure. Because these models are
complex and depend on computer simulation in which many
arbitrary assumptions need to be made in order for the simu-
lations to work, it is often hard to judge how well they ac-
count for various phenomena. Certainly, at our present state
of knowledge, it is quite difficult to decide whether this
nonrepresentational approach is an improvement on the
more traditional representational models (see Besner,
Twilley, McCann, & Seergobin, 1990; Coltheart et al., 1990;
Seidenberg & McClelland, 1990). For the purposes of our
present discussion, a major difference in emphasis between
the models is that for the connectionist models, processes that
would look like the phonological route in the more traditional
models enter into the processing of regular words, and
processes that would look like direct lexical look-up enter
into the processing of pseudowords.
Sound Codes and the Access of Word Meanings
In the previous section we discussed how readers access a vi-
sual word’s sound codes. However, a much more important
question is how readers access a visual word’s meaning (or
meanings). As previously indicated, this has been a highly
contentious issue on which respected researchers have stated
quite differing positions. For example, Kolers (1972) claimed
that processing during reading does not involve readers’
formulating articulatory representations of printed words,
whereas Gibson (1971) claimed that the heart of reading is
the decoding of written symbols into speech. Although we
have learned a great deal about this topic, the controversy
represented by this dichotomy of views continues, and re-
searchers’ opinions on this question still differ greatly.
Some of the first attempts to resolve this issue involved
the previously discussed lexical decision task. One question
that was asked was whether there was a difference between
regularly and irregularly spelled words, under the tacit as-
sumption that the task reflects the speed of accessing the
meaning of words (Bauer & Stanovich, 1980; Coltheart,
1978). These data unfortunately tended to be highly variable:
Some studies found a regularity effect whereas others did not.
Meyer, Schvaneveldt, and Ruddy (1974) utilized a somewhat
different paradigm and found that the time for readers to de-
termine whether touchwas a word was slower when it was
preceded by a word such as couch(which presumably primed
the incorrect pronunciation) as compared to when it was pre-
ceded by an unrelated word. However, there is now consider-
able concern that the lexical decision task is fundamentally
flawed as a measure of so-called lexical access that is related
to accessing a word’s meaning. The most influential of these
arguments was that this task is likely to induce artificial
checking strategies before making a response (Balota &
Chumbley, 1984, 1985).
A task that gets more directly at accessing a word’s mean-
ing is the categorization task. As noted earlier, in this task,
participants are given a category label (e.g., tree) and then are
given a target word (e.g., beech, beach,orbench) and have to
decide whether it represented a member of the preceding cat-
egory (Van Orden, 1987; Van Orden, Johnston, & Hale, 1988;
Van Orden, Pennington, & Stone, 1990). The key finding was
that participants had difficulties rejecting homophones of true
category exemplars (e.g. beach). Not only were they slow in
rejecting these items, they typically made 10–20% more er-
rors on these items than on control items that were visually
similar (e.g., bench).In fact, these errors persisted even when
people were urged to be cautious and go slowly. Moreover,
this effect is not restricted to word homophones. A similar,
although somewhat smaller effect was reported with pseudo-
homophones (e.g., brane). Moreover, in a similar semantic
relatedness judgment task (i.e., decide whether the two words
on the screen are semantically related), individuals are slower
and make more errors on false homophonepairs such as
pillow-bead(Lesch & Pollatsek, 1998). (Bead is a false ho-
mophone of pillow because beadcould be a homophone of
bed,analogously to head’s rhyming with bed.) These find-
ings with pseudohomophones and false homophones both in-
dicate that it is unlikely that such results are merely due to
participants’ lack of knowledge of the target words’ spelling,
and that assembled phonology plays a significant role in ac-
cessing a word’s meaning.
Still, in order for sound codes to play a crucial role in the
access of word meaning, they must be activated relatively
early in word processing. In addition, these sound codes
must be activated during natural reading, and not just when
words are presented in relative isolation (as they were in the
aforementioned studies). To address these issues, Pollatsek,
Lesch, Morris, and Rayner (1992) utilized aboundarypara-
digm (Rayner, 1975) to examine whether phonological